{"id":"W2121164189","doi":"10.1890/08-0446.1","title":"Coexistence and limiting similarity of consumer species competing for a linear array of resources","year":2009,"lang":"en","type":"article","venue":"Ecology","topic":"Plant and animal studies","field":"Agricultural and Biological Sciences","cited_by":59,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Vienna Science and Technology Fund","keywords":"Coexistence theory; Competition (biology); Niche; Resource (disambiguation); Ecology; Competitive exclusion; Limiting; Range (aeronautics); Competitor analysis; Extinction (optical mineralogy); Similarity (geometry); Abiotic component; Competition model; Interspecific competition; Niche differentiation; Ecological niche; Biology; Economics; Microeconomics; Computer science; Paleontology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001310876,0.00004740006,0.0001797299,0.000004469797,0.00009496885,0.000003229046,0.00005785138,0.00003649615,0.00001778085],"category_scores_gemma":[0.0001530985,0.00001925472,0.00003006021,0.00004325908,0.0001185617,0.00001492315,0.00001957763,0.00003197364,3.832777e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000001963996,"about_ca_system_score_gemma":0.000001299439,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001326226,"about_ca_topic_score_gemma":0.0005788901,"domain_scores_codex":[0.9996088,0.00002057935,0.000134069,0.00009251261,0.00003326427,0.0001108239],"domain_scores_gemma":[0.9992518,0.0005865166,0.00009521384,0.000007502492,0.00004301303,0.00001596008],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0000702744,0.00007063858,0.2298172,0.00002026636,0.00001306647,9.647453e-7,0.0003615665,6.831968e-7,0.7653371,0.0006201953,0.0001221404,0.003565958],"study_design_scores_gemma":[0.0001011391,0.0007309461,0.9800228,0.00001771607,0.000008772126,0.000002558681,0.0008523941,0.00003074527,0.009325332,0.0003892499,0.008459641,0.00005865424],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9969347,0.0002396462,9.222179e-7,0.0007170421,0.00001247992,0.00006936926,0.00003987502,0.000008243974,0.001977704],"genre_scores_gemma":[0.9991579,0.00008154177,0.0005553902,0.0001014742,0.00006094952,0.000001302864,0.0000030069,1.505098e-7,0.0000383043],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7560118,"threshold_uncertainty_score":0.07851846,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06724335281022048,"score_gpt":0.2397540357273586,"score_spread":0.1725106829171381,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}